Call centers are generally complex and challenging—for both callers and management. Long before reaching a human operator, a caller frequently interacts with a voice-response system that collects information from the caller to facilitate the call with the operator. Some callers are able to complete a transaction by interacting with the voice-response system without need of an operator. For example, a caller might obtain a bank account balance simply by asking the voice-response system for “current balance” and speaking the caller's account number.
On the other hand, many voice-response interactions are unsuccessful. Often, callers are asked to repeat themselves many times before finally being routed to an operator. When the caller is misunderstood, the call is misrouted or delayed. In such circumstances, callers can become frustrated and hang up.
Call center managers are perennially concerned with lost, delayed, and misrouted calls. Numerous reporting and analysis tools are available in the prior art that are directed at gathering and presentation of statistics for call center performance.
One innovation in call center reporting tools is the “flowgraph.” A flowgraph is a pictorial representation of the salient operational aspects of a call as it flows through a call center. See, e.g., U.S. Pat. No. 7,103,158; U.S. Patent Application Publication No. 20070133777 A1; U.S. Patent Application Publication No. 20090245493 A1. A flowgraph displays a number of useful elements that pertain to the call's flow, such as a prompt event, a response event, a path taken by a call from a prompt event to a response event, a disconnect event, relevant statistics, etc. For example, a flowgraph can show how many calls were hung up before the caller received service or how many calls flowed from a first prompt to a second prompt.
Generally, the voice-response system in a call center asks the caller to speak a request. Sometimes the caller is asked to input digits from a telephone keypad. The caller's speech and telephone digits are referred to as the “utterance.” The voice-response system's technology recognizes the caller's utterance and responds accordingly.
Based on its interpretation of what it heard, the voice-response system routes the call within the call center. For example, a caller who said “current balance” is routed to entering an account number or a password. When the voice-response system does not understand the caller's utterance, it usually asks for repetition. It may ask the caller to repeat three, four, or maybe a dozen times before routing the call to an operator. Or it may misroute the call.
One reason for improperly understanding a caller's utterance may be the mis-calibration of the voice recognition parameters. Another reason may be that the caller asks for an option that the system does not offer, such as asking for “service” when the only options are “current balance” and “teller.” Another reason may be that the caller is asking for a proper option but with an accent or in a language that the system does not understand.
Frequently, the only way to address these issues is to listen to the utterance. Call centers can record caller utterances for subsequent analysis. Some call centers record each call from beginning to end, including the caller's utterances, the prompts, and the system responses that occurred through the duration of the call. These recordings of a call from end to end are useful, but can be difficult to analyze in large numbers. Considering the large volume of calls experienced by a call center, and the fact that a single call may result in numerous utterances as it flows through the voice-response system, a call center can quickly accumulate a huge number of recorded utterances or end-to-end recordings.
Listening to utterances is time-consuming for the analyst tasked with finding possible deficiencies in a voice-response system. For example, an analyst's flowgraph shows that ten percent of incoming calls are hung up by callers after the first prompt. This is useful information, but is insufficient to diagnose the reasons. Delving more deeply into the problem is daunting. First, the analyst must identify each call that hung up after the first prompt. Next, the analyst must determine how many utterances were recorded for each relevant call. Then, the analyst must search through the mass of recorded utterances in the call center to find every utterance of interest. Finally, the analyst is ready to listen to the selected utterances and complete the analysis. This process is lengthy and prone to error. Therefore, a need exists for a more streamlined approach for analyzing utterances.